Major depression ranks among the leading biobehavioral risk factors for cardiovascular (CV) morbidity and mortality. Research has revealed several pathways through which depression increases CV risk including health behaviors and psychosocial functioning. That depression remains a significant predictor of CV disease (CVD) after intervening to improve health behaviors and psychosocial functioning in adults with depression suggests that additional, important risk factors have yet to be identified. We have developed a conceptual model that extends previous research on depression and CV risk by considering sleep as a novel biobehavioral mediator through which depression increases CV risk. We hypothesize that sleep disturbance, including decreased sleep duration, continuity and depth and increased sleep disordered breathing contribute to the increased CV risk observed in adults with major depression. Importantly, each of these components of sleep is modifiable and may represent promising therapeutic targets for reducing the cardiovascular consequences of major depression. The proposed 5-year study will evaluate these relationships in a well-characterized cohort of 200 adults with a history of recurrent major depressive disorder (MDD) who underwent psychiatric assessments and sleep studies in our laboratory approximately 10 to 30 years ago (T1). Participants, who were medically healthy without clinical cardiovascular disease at T1, exhibited profound sleep disturbances that persisted during remission. Members of this cohort have expressed great interest in the proposed follow-up study (T2). Proposed T2 measures include follow-up psychiatric assessments and sleep studies coupled with assessment of CV risk and subclinical disease including indices of autonomic imbalance, endothelial dysfunction, preclinical atherosclerosis and the metabolic syndrome. We will also assess health behaviors, psychosocial functioning and potential confounding variables. Together, these data will provide the first test of the hypothesized paths in our conceptual model. Our primary aim is to use T1 depression and sleep data in conjunction with T2-assessed CV outcomes to evaluate whether PSG-assessed sleep disturbance attenuates the prospective relationship between depression and CV risk and subclinical disease. Our secondary aim is to evaluate both wake and sleep pathways in the same model, using data collected at T2, including objective assessment of physical activity. The use of multiple-group structural equation models will provide the opportunity to evaluate whether relationships among depression, sleep disturbance and CV risk/subclinical disease differ by age and gender (exploratory aim). In future studies, experimental approaches will be needed to establish sleep as a causal pathway, identify the biological mechanisms through which specific components of disturbed sleep in depressed individuals increase CV risk, and develop evidence-based sleep interventions to prevent or attenuate the cardiovascular consequences of major depression.